What You Need to Know about Machine Learning
By Gabriel A. Canepa
This eBook offers you the perfect place to lay the foundation for your work in the world of Machine Learning, providing the basic understanding, knowledge, and skills that you can build on with experience and time.
What you will learn:
- Discover the various forms Machine Learning, and take that which will benefit you the most
- Pick up the Python tools you need to know: from pandas to scikit-learn
- Learn the relationship between machine learning and big data
- Understand and identify potential real-world scenarios where machine learning can be applied
- Lay the foundations to get started in the wide world of machine learning
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HTML5 Graphing and Data Visualization Cookbook
By Ben Fhala
Get a complete grounding in the exciting visual world of Canvas and HTML5 using this recipe-packed cookbook. Learn to create charts and graphs, draw complex shapes, add interactivity, work with Google maps, and much more.
What you will learn:
- Creating graphics in Canvas 2D and draw complex shapes
- Building most of the common charts through step-by-step recipes
- Adding interactivity to canvas elements and create your own JavaScript animation engine
- Discovering many fantastic charting solutions and learn how to deal with their capabilities and how to change them as well
- Learning how to work with Google maps , Google Charts, and Google Docs API
- Integrating your data into live data, xml driven data, objects, and strings
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Building Machine Learning Systems with Python
By Willi Richert, Luis Pedro Coelho
Expand your knowledge of Python data with the power of machine learning with this eBook. Find out how to use cutting-edge Python machine learning algorithms to reveal the hidden insight in your data. You’ll learn how to build machine learning for text, images, and sounds with free open-source tools and libraries.
What you will learn:
- Build a classification system that can be applied to text, images, or sounds
- Use Numpy, ScipY, scikit-learn, and Matplotlib: Python open-source libraries for data and machine learning
- Employ Amazon Web Services to run analyses on the cloud
- Recommend products to users based on past purchases
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Practical Data Analysis
By Hector Cuesta
This eBook is designed to give you the knowledge you need to start succeeding in data analysis. Discover the tools, techniques and algorithms you need to transform your data into insight.
What you will learn:
- Work with data to get meaningful results from your data analysis projects
- Visualize your data to find trends and correlations
- Build your own image similarity search engine
- Learn how to forecast numerical values from time series data
- Create an interactive visualization for your social media graph
- Explore the MapReduce framework in MongoDB
- Create interactive simulations with D3js
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Machine Learning with R
By Brett Lantz
Tech consultants and BI experts will charge a lot to help you turn data into actionable insights. This eBook will help you do just that – without costing a thing. Your business can’t afford to waste its data – and you shouldn’t waste this opportunity to kickstart your skillset.
What you will learn:
- Get to grips with the basics of machine learning
- Find out how to classify data using nearest neighbor methods
- Learn Bayesian methods to classify data
- Predict values using decision trees, rules, and support vector machines
- Model data using neural networks
- Join a global community of statisticians and data scientists putting R to work to produce stunning insights
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